Komparasi Model Prediksi Daftar Ulang Calon Mahasiswa Baru Menggunakan Metode Decision Tree Dan Adaboost

Jurnal Sisfokom (Sistem Informasi dan Komputer)

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Title Komparasi Model Prediksi Daftar Ulang Calon Mahasiswa Baru Menggunakan Metode Decision Tree Dan Adaboost
Creator Rabbani, Muhammad Naufal
Yusuf, Ahmad
Rolliawati, Dwi
Subject System Information
Classification, Adaboost, Ensemble Learning, Enrollment
Data Mining
Description Every year, all the colleges hold new student enrollment. It is needed to start a new school academic year. Unfortunately, the number of students who resigned is considerably high to reach 837 students and caused 324 empty seats. The college’s stakeholders can minimize the resignation number if the selection phase of new students is done accurately.  Making a  machine learning-based model can be the answer. The model will help predict which candidates who potentially complete the enrollment process. By knowing it in the first place will help the management in the selection process. This prediction is based on historical data. Data is processed and used to train the model using the Adaboost algorithm. The performance comparison between Adaboost and Decision Tree model is performed to find the best model. To achieve the maximum performance of the model, feature selection is performed using chi-square calculation. The results of this research show that the performance of Decision Tree is lower than the performance of the Adaboost algorithm. The Adaboost model has f-measure score of 90.9%, precision 83.7%, and recall 99.5%. The process of analyzing the data distribution of prospective new students was also conducted. The results were obtained if prospective students who tended to finish the enrollment process had the following characteristics:  graduated from an Islamic school, 19-21 years old, parents' income was IDR 1,000,000 to IDR. 5,000,000, and through the SBMPTN program.
Publisher ISB Atma Luhur
Date 2021-01-14
Type info:eu-repo/semantics/article
Peer-reviewed Article
Adaboost and Decision Tree
Format application/pdf
Identifier http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/939
Source Jurnal Sisfokom (Sistem Informasi dan Komputer); Vol 10, No 1 (2021): MARCH; 18-24
Language eng
Relation http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/939/703

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